Efficient and compact representations of head related transfer functions

Abstract

These days most reproduced sound is consumed using portable devices and headphones, on which spatial binaural audio can be conveniently presented. One way of converting from conventional loudspeaker formats to binaural format is through the use of Head Related Transfer Functions (HRTFs), but head-tracking is also necessary to obtain a satisfactory externalisation of the simulated sound field. Typically a large HRTF dataset is required in order to provide enough measurements for a continuous virtual auditory space to be achieved through simple linear interpolation, or similar.\\
This work describes an investigation into the use of alternative compact and efficient representations of an HRTF dataset measured in the azimuthal plane. The two main prongs of investigation are the use of orthogonal transformations in a decompositional approach, and parametric modelling approach that utilises techniques often associated with speech processing. The latter approach is explored through the application of a linear prediction derived all-pole model method and a pole-zero model design method proposed by Steiglitz and McBride \citep{Steiglitz1965}. The all-pole model is deemed to offer superior performance in matching the measured data after compression of the HRTF set through computer simulation results, whilst a preliminary subjective validation of the pole-zero models, that contrary to theoretical driven expectations, performed considerably worse in computer simulation experiments, is conducted as a pilot study.\\
Consideration is also given to a method of secondary compression and interpolation that utilises the Discrete Cosine Transform applied to the angular dependent components derived from each of the approaches. It is possible that these techniques may also be useful in developing efficient schemes of custom HRTF capture.